Concerning the relationships between genes, risk factors and immunity in Alzheimer's disease, Autism, Bipolar disorder , multiple sclerosis, Parkinson's disease, schizophrenia and chronic fatigue
Researchers identify key genes and prototype predictive test for schizophrenia - IU Communications - School of Medicine
We have used a translational convergent functional genomics (CFG)
approach to identify and prioritize genes involved in schizophrenia, by
gene-level integration of genome-wide association study data with other
genetic and gene expression studies in humans and animal models. Using
this polyevidence scoring and pathway analyses, we identify top genes
(DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as
ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A,
NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell
adhesion, glutamate receptor signaling, G-protein–coupled receptor
signaling and cAMP-mediated signaling as key to pathophysiology and as
targets for therapeutic intervention. Overall, the data are consistent
with a model of disrupted connectivity in schizophrenia, resulting from
the effects of neurodevelopmental environmental stress on a background
of genetic vulnerability. In addition, we show how the top candidate
genes identified by CFG can be used to generate a genetic risk
prediction score (GRPS) to aid schizophrenia diagnostics, with
predictive ability in independent cohorts. The GRPS also differentiates
classic age of onset schizophrenia from early onset and late-onset
disease. We also show, in three independent cohorts, two European
American and one African American, increasing overlap, reproducibility
and consistency of findings from single-nucleotide polymorphisms to
genes, then genes prioritized by CFG, and ultimately at the level of
biological pathways and mechanisms. Finally, we compared our top
candidate genes for schizophrenia from this analysis with top candidate
genes for bipolar disorder and anxiety disorders from previous CFG
analyses conducted by us, as well as findings from the fields of autism
and Alzheimer. Overall, our work maps the genomic and biological
landscape for schizophrenia, providing leads towards a better
understanding of illness, diagnostics and therapeutics. It also reveals
the significant genetic overlap with other major psychiatric disorder
domains, suggesting the need for improved nosology.
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